An AI strategy that actually ships.
Every board wants an AI strategy. Most of what gets sold under that name is a deck. I build the other kind: a plan tied to your P&L, written by the fractional AI CTO who then stays to build it, hands-on, until the leverage shows up in the numbers.
What an AI strategy actually is.
An AI strategy is a plan for where AI makes your business measurably better, and what it takes to get there. Which workflows it should run. What it does to your cost structure. What your architecture, your data, and your team have to become. It's a business document with an engineering spine.
Most AI strategies die at the same spot: the handoff. A firm writes the vision, leaves, and the pilots stall in the gap between the deck and the codebase. I close that gap by refusing to hand off. I write the strategy as your fractional AI CTO, then lead the build until the results are in production and on the P&L.
The work is remote-first. I serve US companies from Eastern Time, with same-day overlap across every US time zone. New to the term? Read the plain-English guide.
Also known as: AI strategy consulting, enterprise AI strategy, AI roadmap, AI advisory, fractional AI CTO, AI transformation strategy.
You have AI activity.
You don't have an AI strategy.
The symptoms vary. The missing piece is usually the same: nobody senior owns the plan.
Pilot purgatory
You've run six AI pilots. None reached production, and nobody can say why the seventh will be different.
Board pressure, no plan
Investors ask about your AI strategy every quarter. What you actually have is a copilot license and a slide.
AI theater
There's a chatbot on the website and a demo in the all-hands. The operation still runs the way it did in 2022.
Spend without leverage
Tokens, tools, vendors and headcount are going out the door, and the leverage they were supposed to buy isn't showing up anywhere you can measure.
Six answers, in writing.
A strategy you can build against. Every section is specific enough to be wrong, which is what makes it useful.
Opportunity audit
Where AI creates real leverage in your product and operations, and where it's a distraction. Grounded in your data and your margins.
The AI roadmap
A sequenced plan tied to revenue and cost, with the unglamorous prerequisites, data, evals, security, scheduled instead of ignored.
Architecture & models
Build vs buy, which models, agentic or not, and the eval, observability and cost controls that keep it honest in production.
AI economics
Unit costs, token spend, and the cost curves that decide what's viable. A strategy that ignores the economics is a demo.
Team & operating model
Who you hire, who you upskill, and how the workflows change so AI becomes the default way work gets done.
Governance & safety
Usage policy, data boundaries and review gates, so you can move fast without betting the company on an unreviewed prompt.
Strategy as a document
vs. strategy as an operating change.
Both get called "AI strategy." Only one survives contact with your codebase.
Written, presented, shelved
- , Authored by a firm that leaves before the build starts
- , Use cases ranked by excitement, not economics
- , No owner once the engagement ends
- , Pilots forever; production never
Written by the person who builds it
- →One accountable fractional AI CTO from plan to production
- →Use cases ranked by P&L impact and feasibility
- →Architecture, evals and cost control specified up front
- →Leverage you can see in cost, speed and quality
The strategy isn't the deliverable. The company that runs differently a year later is the deliverable. Everything else is theater.
What it costs, published.
Strategy and delivery are priced separately, so you can start small and scale commitment as the plan proves out. I publish my numbers so you can self-qualify before we talk.
The Diagnostic
The Business-Down read on your system, org, spend and AI leverage, plus a 90-day plan you can act on with or without me. The best first step.
AI-Native Roadmap & Architecture Sprint
The full AI strategy: opportunity audit, sequenced roadmap, architecture and model choices, and the economics. Ready to build against.
Fractional AI CTO
I stay to lead the build: architecture, hiring, delivery and the operating-model change. Hands-on, until the leverage is real.
All prices USD. Ongoing leadership shares tiers with the Fractional CTO engagement — same person, same method. Market context: what an AI strategy costs, explained. Email me ↗
Related reading & paths.
AI-Native Transformation
Where the strategy leads: rebuilding how the product is built and how the org runs so AI is the default.
Fractional CTO
The flagship engagement. Senior, AI-native technology leadership without the full-time hire, with published pricing.
Escaping AI pilot purgatory
Why pilots stall, and what the organizations that actually reach production do differently.
What founders & boards ask.
What is an AI strategy?
An AI strategy is a plan for where AI creates measurable business leverage and what it takes to get there: which workflows and products it should run, the architecture and models behind it, the economics, the team, and the governance. A real one is tied to the P&L and sequenced into a roadmap you can build against. If it can't survive contact with your codebase and your cost structure, it's a vision statement, not a strategy.
What does an AI strategy consultant do?
A typical AI strategy consultant audits your business, identifies AI use cases, and delivers a recommendation. I do that work and then stay to build it. As a fractional AI CTO I write the strategy, make the architecture and model choices, hire and upskill the team, and lead delivery until the systems are in production and the leverage is measurable.
What is a fractional AI CTO?
A fractional AI CTO is an experienced technology executive who leads your AI strategy and its execution part-time, instead of as a full-time hire. You get senior judgment on AI architecture, build-vs-buy, team and governance, plus hands-on delivery, without a six-month executive search. It's the fractional CTO model focused on making AI the default in how the company builds and operates.
How much does an AI strategy cost?
My pricing is published. A fixed-fee Diagnostic starts at $20,000 and takes two to four weeks. The full AI-Native Roadmap & Architecture Sprint, the complete strategy with architecture and economics, starts at $35,000. Ongoing leadership to build it runs $18,000 per month at roughly two days a week. All prices are USD.
How long does it take to develop an AI strategy?
The Diagnostic takes two to four weeks. The full roadmap and architecture sprint takes four to six weeks. That's enough to know where the leverage is, what to build first, and what it will cost. Execution is where the real time goes; engagements that continue into delivery usually run six to eighteen months.
How is this different from hiring a big consulting firm?
Two ways. You work with me directly: no bench, no account manager, and the person who writes the strategy is the person who builds it. And the strategy is written to be shipped: it specifies how each system will be evaluated and what it will cost to run, because I'm the one accountable for shipping it.
Do we need an AI strategy or an AI-native transformation?
The strategy is where you start; the transformation is where it leads. The strategy tells you where AI pays and what to build first. An AI-native transformation then rebuilds how the whole company works so AI is the default rather than an add-on. In practice one flows into the other, and I lead both.
Need an AI strategy that
survives production?
Tell me where you're stuck: pilots that stall, board pressure, or a blank page. I'll tell you honestly what a real plan looks like.